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@PHDTHESIS{Loriemi:1023832,
      author       = {Loriemi, Amin},
      othercontributors = {Jacobs, Georg and Schmitt, Robert H.},
      title        = {{M}onitoring von {H}auptlagerlasten in
                      {W}indenergieanlagen},
      school       = {Rheinisch-Westfälische Technische Hochschule Aachen},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {RWTH Aachen University},
      reportid     = {RWTH-2025-10775},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2025},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University 2026; Dissertation, Rheinisch-Westfälische
                      Technische Hochschule Aachen, 2025},
      abstract     = {The main bearing loads of wind turbines are not monitored
                      as standard. To date, there is no economical and validated
                      method for this. However, knowledge of these loads can help
                      to reduce the levelized cost of energy for wind turbines. By
                      knowing the main bearing loads, the lifetime of the main
                      bearings can be calculated. By proving that the bearings
                      have a sufficient remaining lifetime, it is possible to
                      continue operating the wind turbine beyond the planned
                      lifetime without expensive bearing replacements. After
                      examining the advantages and disadvantages of various
                      concepts, a load estimation system based on displacement
                      signals was selected. This system was developed and
                      validated through test bench experiments. Suitable
                      displacement signals for load estimation were identified
                      through correlation analyses. Various regression models were
                      investigated. These models were first trained with test
                      bench measurements. In comparison, linear regression was
                      identified as the preferred regression model due to its
                      simplicity and sufficient accuracy. An alternative and more
                      economical development of the regression models based on
                      physical simulations of the rotor suspension was considered.
                      It was found that detailed FEM modelling is required to
                      achieve the necessary accuracy. Simplified models were
                      insufficient. Nevertheless, not all main bearing load
                      components could be determined with the required accuracy.
                      In addition, sensitivity analyses carried out showed that
                      uncertainties in the model parameters represent significant
                      sources of error. A main bearing load estimation using
                      displacement signals is possible with a co-efficient of
                      determination between 0.83 and 0.9. A subsequent bearing
                      lifetime estimation results in an error of up to $19\%.$ By
                      additionally taking strain signals into account, a load
                      estimation with a coefficient of determination between 0.89
                      and 0.94 can be achieved. This allows the bearing lifetime
                      estimation to be im-proved to an error of up to $6\%.$
                      However, disadvantages regarding the sensor technology for
                      strain measurement still remain.},
      cin          = {411710},
      ddc          = {620},
      cid          = {$I:(DE-82)411710_20190404$},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2025-10775},
      url          = {https://publications.rwth-aachen.de/record/1023832},
}